Janice E. Carrillo

Single versus multiple supplier sourcing strategies

Successful supply chain management necessitates an effective sourcing strategy to combat uncertainties in both supply and demand. In particular, supply disruption results in excessive downtime of production resources, upstream and downstream supply chain repercussions, and eventually a loss in the market value of the firm. In this paper we analyze single period, single product sourcing decisions under demand uncertainty. Our approach integrates product prices, supplier costs, supplier capacities, historical supplier reliabilities and firm specific inventory costs. A unique feature of our approach is the integration of a firm specific supplier diversification function. We also extend our analysis to examine the impact of minimum supplier order quantities. Our results indicate that single sourcing is a dominant strategy only when supplier capacities are large relative to the product demand and when the firm does not obtain diversification benefits. In other cases, we find that multiple sourcing is an optimal sourcing strategy. We also characterize a non-intuitive trade-off between supplier minimum order quantities, costs, and supplier reliabilities. Finally, we examine the robustness of our results through an extensive numerical analysis of the key parameters of our model.

Investing in product development and production capabilities: The crucial linkage between time-to-market and ramp-up time

Shorter product life cycles, more rapid product obsolescence, and the increasing intensity of global competition have driven firms to strive for a more rapid introduction of new products to market. We introduce a normative model which yields insights concerning several key new product development (NPD) decisions. First, we examine investment strategies related to the timing and duration for investments in both design and process capacity over a given planning horizon. Second, the model offers guidance regarding the optimal time-to-market and ramp-up time necessary to meet peak demand for the new product. The model thus provides both theoretical and managerial insights into the crucial linkage between time-to-market and ramp-up time decisions. Finally, the implications of several specific NPD investment mechanisms on these NPD metrics are explored.

β-Robust scheduling for single-machine systems with uncertain processing times

In scheduling environments with processing time uncertainty, system performance is determined by both the sequence in which jobs are ordered and the actual processing times of jobs. For these situations, the risk of achieving substandard system performance can be an important measure of scheduling effectiveness. To hedge this risk requires an explicit consideration of both the mean and the variance of system performance associated with alternative schedules, and motivates a β-robustness objective to capture the likelihood that a schedule yields actual performance no worse than a given target level. In this paper we focus on β-robust scheduling issues in single-stage production environments with uncertain processing times. We define a general β-robust scheduling objective, formulate the β-robust scheduling problem that results when job processing times are independent random variables and the performance measure of interest is the total flow time across all jobs, establish problem complexity, and develop e...

Managing Knowledge-Based Resource Capabilities Under Uncertainty

A firms ability to manage its knowledge-based resource capabilities has become increasingly important as a result of performance threats triggered by technology change and intense competition. At the manufacturing plant level, we focus on three repositories of knowledge that drive performance. First, the physical production or information systems represent knowledge embedded in the plants technical systems. Second, the plants workforce has knowledge, including diverse scientific information and skills, to effectively operate the technical systems. Third, the firms managerial systems embody knowledge in the form of goals, reward systems, and control and coordination systems. Taken together, we consider the technical systems, workforce knowledge, and the managerial systems as the plants knowledge-based resource capability.Two normative models are introduced offering insight on how plant performance is impacted by investments in workforce knowledge (training) or the technical systems (process change). The models explicitly recognize that the outcome of investments in knowledge-based change is uncertain due to factors including technical problems, worker resistance, and limited financial resources. Also, we recognize that workforce knowledge may be deployed to mitigate the outcome uncertainty encountered with process change.Investments in knowledge-based change cannot be fully understood in isolation of the managerial systems. In one model, the plant manager is motivated by an incentive system that rewards the realization of a threshold goal, whereas in the other model the incentive system emphasizes the realization of meeting a particular target goal. We also investigate the impact of the managers view of uncertainty (her willingness to absorb risk), which is influenced by the managerial systems. Results show that different characterizations of the managerial systems have a profound effect on managerial behavior and plant-level performance.

Heuristics for sourcing from multiple suppliers with alternative quantity discounts

In this paper, we analyze the impact of supplier pricing schemes and supplier capacity limitations on the optimal sourcing policy for a single firm. We consider the situation where the total quantity to be procured for a single period is known by the firm and communicated to the supplier set. In response to this communication, each supplier quotes a price and a capacity limit in terms of a maximum quantity that can be supplied to the buyer. Based on this information, the buyer makes a quantity allocation decision among the suppliers and corresponding to this decision is the choice of a subset of suppliers who will receive an order. Based on industry observations, a variety of supplier pricing schemes from the constituent group of suppliers are analyzed, including linear discounts, incremental units discounts, and all units discounts. Given the complexity of the optimization problem for certain types of pricing schemes, heuristic solution methodologies are developed to identify a quantity allocation decision for the firm. Through an extensive computational comparison, we find that these heuristics generate near-optimal solutions very quickly. Data from a major office products retailer is used to illustrate the resulting sourcing strategies given different pricing schemes and capacity limitations of suppliers in this industry. We find for the case of capacity constrained suppliers, the optimal quantity allocations for two complex pricing schemes (linear discount, and incremental units discount) are such that at most one selected supplier will receive an order quantity that is less than its capacity.

A framework for process change

Forces such as technology change and increased competition provide opportunities and challenges that drive a firm to continuously evaluate and modify its resource capabilities. As a consequence, a firms process change strategy is of paramount importance for sustained manufacturing success. However, fundamental elements of process change strategy are not well understood. Long term performance benefits associated with potential process change alternatives are often unclear. Moreover, uncertainty exists regarding the actual benefits that may be attained from various types of process change. Critical issues impacting the proper implementation of process change are frequently underestimated or largely ignored. Therefore, despite the improved performance sought, process change often leads to lower productivity, excessive equipment downtime, and deterioration in quality. As the authors review the relevant empirical and normative literature, a framework emerges that characterizes the salient features of a firms process change strategy. The underlying dynamics of process change are explored and strategies are discussed to reduce the short-term disruption and enhance the long-term gain. In particular, the authors demonstrate the importance of creating and applying knowledge to improve the outcome of process change. They describe managerial actions that can be taken to reduce various sources of uncertainty associated with process change. Moreover, they identify key contributions as well as limitations of the existing normative literature on process change. Insights from the empirical literature are given that both support elements of the existing normative models and provide direction for future normative research. Thus, the authors seek to aid practicing managers and researchers alike to better understand the full scope and implications of process change.

Environmental implications for online retailing

Recent press has highlighted the environmental benefits associated with online shopping, such as emissions savings from individual drivers, economies of scale in package delivery, and decreased inventories. We formulate a dual channel model for a retailer who has access to both online and traditional market outlets to analyze the impact of customer environmental sensitivity on its supply. In particular, we analyze stocking decisions for each channel incorporating price dependent demand, customer preference/utility for online channels, and channel related costs. We compare and contrast results from both deterministic and stochastic models, and utilize numerical examples to illustrate the implications of industry specific factors on these decisions. Finally, we compare and contrast the findings for disparate industries, such as electronics, books and groceries.

Fusion Product Planning: A Market Offering Perspective

Devices that integrate multiple functions together are popular in consumer electronic markets. We describe these multifunction devices as fusion products as they fuse together products that traditionally stand alone in the marketplace. In this article, we investigate the manufacturers fusion product planning decision, adopting a market offering perspective that allows us to address the design and product portfolio decisions simultaneously. The general approach adopted is to develop and analyze a profit-maximizing model for a single firm that integrates product substitution effects in identifying an optimal market offering. In the general model, we demonstrate that the product design and portfolio decisions are analytically difficult to characterize because the number of possible portfolios can be extremely large. The managerial insight from a stylized all-in-one model and numerical analysis is that the manufacturer should, in most cases, select only a subset of fusion and single-function products to satisfy the markets multidimension needs. This may explain why the function compositions available in certain product markets are limited. In particular, one of the key factors driving the product portfolio decision is the margin associated with the fusion products. If a single all-in-one fusion product has relatively high margins, then this product likely dominates the product portfolio. Also, the congruency of the constituent single-function products is an important factor. When substitution effects are relatively high (i.e., the product set is more congruent), a portfolio containing a smaller number of products is more likely to be optimal.

Projects with sequential iteration: Models and complexity

Many New Product Development (NPD) projects are inherently complex, making effective management of the tasks, resources, and teams necessary to bring new products to market problematic. Frequently, managers of NPD projects are overwhelmed by complicating factors such as stochastic task times, ill-defined specifications, complex interrelationships between tasks, and information dependencies. Recently, an alternative project management tool called the Design Structure Matrix (DSM) that explicitly takes into account the iterative nature of NPD projects has been proposed. In this paper, we first introduce a mixed-integer linear programming formulation for the numerical DSM. Then, we analyze the numerical DSM and establish the complexity of this class of problems. Finally, numerical analysis of the DSM problem and heuristic approaches is presented that shows that relatively good solutions can be easily obtained, thereby offering managers an efficient alternative solution approach to the original DSM problem.

Introduction to innovation within and across borders: : A review and future directions

Innovation is an integral part of every firms ongoing operations. While new product and service creation is an essential task to ensure a firms immediate success in the marketplace, process and supply chain innovations can also create a unique source of competitive advantage for the future. Encouraging innovative thinking, developing new innovations, and managing the processes by which those innovations are developed are critical aspects of todays firm. Consequently, research which aids in the creation and maintenance of innovative firms is an important topic of inquiry for research communities on innovation management, including the operations management and information systems communities. We review the literature in this important area and offer suggestions for future research on the following topics: innovation within a firm and across the supply chain, technology management, and new product and service development.